<p dir="ltr"><b>Note: </b>Version 3.1 supersedes all previous releases. Version 3.0 has been deprecated due to the discovery of a data inconsistency in the calculation of net longwave radiation in the source code used to generate the dataset. As a result, there is a general positive bias in potential evapotranspiration (ET<sub>0</sub>) and a consequent lower (drier) bias in the Aridity Index (AI) in affected outputs. This issue has been fully corrected in v3.1, and all ET<sub>0</sub> and AI products have been recomputed using the corrected method. We are grateful for the numerous feedback from users and in particular to Dr. Pushpendra Raghav, Research Scientist, Department of Civil Engineering, University of Alabama, for identifying and bringing this issue to our attention. We recommend all users migrate to Version 3.1 and discontinue use of the previous v3.0.</p><p>***********************************************************************************************************************************</p><p dir="ltr"><b>NOTE: </b>The recently released Future Global Aridity Index and PET Database (CMIP_6) is now available at:</p><p dir="ltr">https://doi.org/10.57760/sciencedb.nbsdc.00086</p><p dir="ltr">High-resolution (30 arc-seconds) global raster datasets of average monthly and annual potential evapotranspiration (PET) and aridity index (AI) for two historical (1960-1990; 1970-2000) and two future (2021-2040; 2041-2060) time periods for each of 22 CIMP6 Earth System Models across four emission scenarios (SSP: 126, 245, 370, 585). The database also includes three averaged multi-model ensembles produced for each of the four emission scenarios:</p><p>**************************************************************************************************************************</p><p dir="ltr">The Global Aridity Index (Global-AI) and Global Reference Evapo-Transpiration (Global-ET0) datasets provided in Version 3.1 of the Global Aridity Index and Potential Evapo-Transpiration (ET0) Database (Global-AI_PET_v3.x1) provide high-resolution (30 arc-seconds) global raster data for the 1970-2000 period, related to evapotranspiration processes and rainfall deficit for potential vegetative growth, based upon implementation of the FAO-56 Penman-Monteith Reference Evapotranspiration (ET<sub>0</sub>) equation.</p><p dir="ltr">Aridity Index represent the ratio between precipitation and ET<sub>0</sub>, thus rainfall over vegetation water demand (aggregated on annual basis). Under this formulation, Aridity Index values increase for more humid conditions, and decrease with more arid conditions. The Aridity Index values reported within the <i>Global-AI</i> geodataset have been multiplied by a factor of 10,000 to derive and distribute the data as integers (with 4 decimal accuracy). This multiplier has been used to increase the precision of the variable values without using decimals. The Readme File is provided with a detailed description of the dataset files. A peer-reviewed article is now available with a description of the methodology and a technical evaluation.</p><p dir="ltr">The Global-AI_PET_v3 datasets are provided for non-commercial use in standard GeoTiff format, at 30 arc seconds or ~ 1km at the equator.</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. Version 3 of the Global Aridity Index and Potential Evapotranspiration Database. Scientific Data 9, 409. https://www.nature.com/articles/s41597-022-01493-1</p><p><br></p><p><br></p><p><br></p>
Funding
Chinese Academy of Science (CAS) President’s International Fellowship Initiative (Grant No. 2020vca0025).